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Anders Bjorholm DahlView profile

Professor

• Medical Imaging
• Computer Vision
• Biomedical Engineering
• +6 more

Anders Bjorholm Dahl is a Professor at the Department of Applied Mathematics and Computer Science , DTU Compute , Technical University of Denmark (DTU). His research focuses on medical imaging, computer vision, and biomedical engineering. He leads projects in ultrasound imaging, AI-driven medical diagnostics, and advanced imaging technologies for healthcare applications. Education: Ph.D. in Computer Science (Image Analysis and Computer Vision), DTU (2005–2009) Forestry, Royal Veterinary and Agricultural University (1997–2004) Research Interests: Combines machine learning and advanced imaging techniques to address challenges in medical diagnostics, including ultrasound super-resolution, stenosis detection in coronary angiographies, and material anisotropy analysis. His work bridges anatomy and histology using X-ray tomography and explores AI applications in healthcare. Key Projects: Crowd Counting through Remote Sensing (2025–2027) AI for Extreme Super-Resolution CT (2024–2026) Fighting Cancer with Generative AI (2024–2027) Labs/Teams: Leads the UltraSound and Biomechanics Visual Computing Center for Fast Ultrasound Imaging , focusing on real-time medical imaging solutions.

• Microplastics
• Plastic Pollution
• Environmental Policy
• +3 more

Amila Abeynayaka is a Postdoctoral Fellow at DTU SUSTAIN, Technical University of Denmark, affiliated with the Department of Environmental and Resource Technology. Their research focuses on microplastics pollution, plastic waste management, water quality assessment, and science-policy integration for global environmental governance. Recent work highlights include Investigations into microplastic distribution along Sri Lankan coastlines Development of science-based recommendations for global plastic treaties Material flow analysis of plastic waste in ASEAN countries Amila’s expertise spans life cycle assessment of water technologies, disaster response systems, and environmental data accessibility. They collaborate on regional and international projects addressing plastic pollution and sustainable resource management.

Anders Nymark ChristensenView profile

Associate Professor

• Image Analysis
• Computer Vision
• Medical Imaging
• +7 more

Anders Nymark Christensen is an Associate Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU), specializing in Visual Computing. His work bridges computer vision, medical imaging, and materials science, with a strong focus on explainable AI in clinical applications and structural analysis of complex materials. Institution: Technical University of Denmark (DTU) School: Department of Applied Mathematics and Computer Science Department: Visual Computing Role: Associate Professor Christensen’s research interests include image analysis, computer vision, explainable AI, ultrasound imaging, fetal medicine, and fiber orientation in composites. He applies advanced computational techniques to solve real-world problems in healthcare and materials engineering, particularly through structure tensor analysis and deep learning. His recent publications highlight a strong trend in developing AI tools for clinical decision support in fetal medicine, structural analysis of food and composite materials, and ultrasound imaging. These works span journals such as Scientific Reports , Food Structure , and IEEE Access , reflecting interdisciplinary innovation. Clinical validation of explainable AI for fetal growth scans Characterization of anisotropy in mozzarella cheese Determining fetal orientations from ultrasound video Structure tensor analysis in composites He supervises several PhD students in projects related to AI in skin lesion analysis, cancer detection, and ultrasound imaging. His collaborative network includes key researchers at DTU such as Anders Bjorholm Dahl, Vedrana Andersen Dahl, and Mads Nielsen. He has been involved in significant research grants and is active in both medical and engineering domains, contributing to open datasets and reproducible research. Christensen leads and contributes to numerous active projects, including: Decision Support AI for Skin Lesions (2024–2027) Fighting Cancer with Generative AI (2024–2027) SONAI: Explainable AI in the Clinic (2022–2026) Deep learning for identifying biomarkers in medical images (2022–2025) His work supports UN Sustainable Development Goals related to health, innovation, and responsible consumption, particularly through advancements in medical diagnostics and sustainable materials.

• Software Engineering
• Database Systems
• Medical Imaging
• +3 more

Anders Lassen is a Part-Time Lecturer at the Department of Computer Science , University of Copenhagen, under the Faculty of Science . His academic career combines software engineering with interdisciplinary collaborations in medical imaging and neuroscience . Specializes in database modeling and software complexity analysis Key collaborator in neuroimaging research (SPECT, MRI, GISAXS) Applies computational methods to biomedical and materials science challenges Research trends over two decades show expertise in both software metrics (Function Point Analysis, COCOMO models) and computational neuroscience (dopamine receptor imaging, brain volumetry). His work bridges relational database design and advanced imaging algorithms for biomedical applications. Contact: knh487@di.ku.dk | Mobile: +45 2089 8668

Ulrik Pagh Schultz LundquistView profile

Professor

• Robotics
• Unmanned Aerial Vehicles
• Programming Languages
• +6 more

Ulrik Pagh Schultz Lundquist is a Professor at the Maersk Mc-Kinney Moller Institute, University of Southern Denmark (SDU), where he serves as Head of both the SDU UAS Center and SDU Climate Cluster. With over 123 research outputs spanning robotics, drone technology, and programming languages, Lundquist leads significant initiatives including WildDrone (2023-2026) and Terra Salva (2024-2026), and has established himself as a leading expert in unmanned aerial systems research with extensive field applications in wildlife conservation. Lundquist's research focuses on the intersection of robotics and environmental science, with particular expertise in drone swarms for ecological monitoring. His work bridges theoretical computer science with practical conservation challenges, developing programming languages and formal models specifically for modular robotics systems. Key research thrusts include minimizing wildlife disturbance through optimized drone operations, multi-perspective data collection techniques, and scalable BVLOS (Beyond Visual Line of Sight) systems for conservation areas. His fingerprint analysis reveals strong contributions to domain-specific languages (67%), unmanned aerial vehicles (28%), and object-oriented programming (28%). Recent publications demonstrate a clear trajectory toward practical conservation applications, with increasing emphasis on ethical drone deployment, wildlife disturbance minimization, and operational safety in complex environments. Lundquist's work shows growing integration of swarm intelligence techniques with traditional conservation practices, particularly in African ecosystems as evidenced by field trials at Kenya's Ol Pejeta Conservancy. Lundquist actively leads multiple research projects including WildDrone (focusing on multi-perspective animal monitoring), Terra Salva (terahertz data transmission via drones), and a High Altitude Balloon platform for vegetation monitoring. His professional leadership includes chairing the ACM International Conference on Generative Programming Steering Committee (2019-2022) and significant roles in COST Action IC1405 (2015-2019). As a highly visible expert, he has contributed to 107 media appearances, frequently advising on drone policy including Denmark's regulatory approaches to drone safety and wildlife protection. As Head of the SDU UAS Center, Lundquist directs a multidisciplinary research team specializing in conservation drone technology. The center maintains strong international collaborations, particularly with African conservation organizations, focusing on developing drone swarm methodologies that balance data quality with minimal ecological disturbance. Current team efforts prioritize field-deployable systems that can operate effectively in remote natural habitats while providing conservationists with high-quality multi-perspective monitoring capabilities.

Cancan WangView profile

Lecturer

• IT Governance
• Sustainability Transition
• Data Governance
• +5 more

Cancan Wang serves as a Lecturer in Digitalisation, Democracy, and Governance at the IT University of Copenhagen's REFLECT Center for Climate IT. Her academic work bridges technology policy, sustainability transitions, and data governance frameworks across public and private sectors. Her research focuses on IT Governance , Data Commons , and Political Economy of Data , with particular expertise in China's digital policy landscape and ESG data infrastructure. Current investigations examine how data systems enable sustainability transformations while navigating regulatory complexities in fintech and climate governance contexts. Wang's publication trends reveal intensifying focus on data-driven sustainability (40% of 2023-2025 output), China's governance models (25%), and regulatory responses to AI (20%). Her work increasingly integrates cross-disciplinary perspectives from political science, information systems, and environmental studies. Awarded the Kauffman Best Paper Award Runner Up (2022) for contributions to information systems research, her recognition highlights growing influence in digital governance scholarship. Principal Investigator for GreenITSME (2025-2026) exploring service-oriented green IT models for SMEs Co-Investigator in DecouplingIT (2022-2027), a €4.2M EU-funded climate crisis mitigation project Project lead for DEED-Fintech (2024) developing ESG data governance education for startups Wang actively shapes discourse through media engagements including Børsen commentary on AI legislation and Danish public radio appearances analyzing data sovereignty. Her leadership extends to chairing the 2023 Conference on Sustainability and Data and organizing the CDW Global Comparisons Masterclass series.

Luca SimeoneView profile

Associate Professor

• Strategic Design
• Design Management
• Innovation Management
• +7 more

Luca Simeone is an Associate Professor at Aalborg University's Department of Architecture, Design and Media Technology within The Technical Faculty of IT and Design. He specializes in strategic design, design management, and innovation management, focusing on resilience, transition thinking, and sustainable futures. His research bridges design, arts, and urban planning, emphasizing participatory methods and systemic approaches. Education: PhD in Interaction Design from Malmö University (2016), with a focus on academic entrepreneurship and design labs. Extensive teaching experience at Harvard, MIT, Polytechnic University of Milan, and others. Research Interests: Strategic design processes, circular economy, foresight, and design-driven innovation. His work explores how design can foster resilience in communities, support long-term strategic planning, and address urban sustainability challenges through participatory frameworks. Recent Article Trends: Focus on multispecies futuring, temporal analysis in design, and bridging design with urban innovation. Themes include visual mapping for strategic articulation, participatory methods for urban regeneration, and leveraging design for cross-sector collaboration. Awards: Best Ergonomics in Design Article Award (2022) Teacher of the Year (2020) Winner of the Data Challenge (2018) Advising & Grants: Supervised 2 PhD students and led projects such as CD4T: Co-Design 4 Transitions and Climaborough – Building Green Climate-Neutral City-Hubs . Active in EU-funded initiatives focusing on climate adaptation and urban sustainability. Labs & Teams: Involved in design foresight symposiums and collaborative networks like the Design for Change Special Interest Group (SIG). Co-organizes events exploring designerly approaches to systemic challenges.

Silvia MikschView profile

Professor

• Visualization
• Visual Analytics
• Time-oriented Data Visualization
• +5 more

Silvia Miksch is a University Professor and head of the Research Center for Visual Analytics Science and Technology (CVAST) at the Institute of Software Technology & Interactive Systems, Vienna University of Technology (TU Wien). She previously served as University Professor and head of the Department of Information and Knowledge Engineering at Danube University Krems (2006–2010) and founded the Laura Bassi Centre of Expertise "CVAST" in 2010, funded by the Austrian Federal Ministry of Science, Research, and Economy. Her research focuses on Visualization and Visual Analytics , particularly Focus+Context techniques , interaction design , and time-oriented data analysis . She has made significant contributions to the development of systems that support the exploration of complex temporal and networked data in domains such as economics and finance. The recent publications highlight her work in guidance-enriched visual analytics for economic networks and modeling financial data over time with incremental domain knowledge. These works reflect a strong trend toward integrating user guidance, temporal reasoning, and domain-specific knowledge into visual analytics frameworks. Scientific Awards and Recognition: Established the awarded Laura Bassi Centre of Expertise "CVAST – Center for Visual Analytics Science and Technology" Advising and Service: While no formal students are listed, Silvia Miksch has played a major leadership role in shaping the research landscape. She has served as conference paper co-chair for IEEE VAST 2010 and 2011, EuroVis 2012, and has been on the editorial boards of top journals including Artificial Intelligence in Medicine , IEEE TVCG , Computer Graphics Forum , and Journal of Biomedical Informatics . She actively contributes to the strategic direction of the field through roles in the VAST steering committee and the VIS Executive Committee (VEC). Labs and Teams: She leads CVAST (Center for Visual Analytics Science and Technology), a research center dedicated to advancing visual analytics through interdisciplinary collaboration and innovation.

Lars Pilgaard MikkelsenView profile

Associate Professor

• Composite Materials
• Wind Energy Systems
• Finite Element Analysis
• +3 more

Lars Pilgaard Mikkelsen is an Associate Professor in the Department of Wind and Energy Systems at the Technical University of Denmark (DTU). His research focuses on numerical finite element simulations and experimental characterization of polymer matrix composites, particularly in wind turbine blade materials. Key areas include fatigue and compression behavior, utilizing tools like Abaqus and 3D x-ray tomography. He has supervised numerous PhD and Master's projects, including topics such as pultruded carbon fiber composites and wind turbine blade redesign. Awards include the Simulia Champion (2020). Mikkelsen is involved in various committees and editorial roles, including the Wind Energy Science Journal and the Danish Center for Applied Mathematics and Mechanics. His work contributes to UN Sustainable Development Goals related to affordable and clean energy (SDG 7) and industry, innovation, and infrastructure (SDG 9). His research bridges computational modeling and experimental techniques to advance material science applications in renewable energy systems.

• Cognitive Psychology
• Visual Perception and Attention
• Multisensory Integration
• +4 more

Steven Blurton is an Associate Professor in the Department of Psychology at the University of Copenhagen's Faculty of Social Sciences, specializing in cognitive psychology with a focus on mathematical modeling of perceptual and decision processes. His research integrates computational approaches with experimental paradigms to investigate fundamental cognitive mechanisms. Research Interests: Visual perception and attention dynamics Multisensory integration across auditory and visual domains Mathematical modeling of response times and decision-making Theory of Visual Attention (TVA) frameworks Sequential sampling models for cognitive processes His recent publications demonstrate an evolving trajectory from foundational work on Wiener diffusion models (2012) toward increasingly sophisticated integrations of response time modeling with multisensory processing and executive function interventions, with significant contributions appearing in Psychological Review , Journal of Mathematical Psychology , and Vision Research . Current research within the KU 2016 "Dynamical Systems" program focuses on unifying accuracy and response time predictions through sequential sampling models. Key Activities: Principal Investigator in the DFF 8018-00014B project "Foundations of Response Time Measurement" (2019-2020) Active member of the Center for Visual Cognition research group His methodological expertise spans computational modeling, experimental design for perceptual tasks, and advanced statistical analysis of cognitive data, with applications spanning basic research and educational interventions.